Working default workflow (file -> celery -> redis -> worker)

docker-compose.yml

@@ -59,6 +59,7 @@ services:
       - PYTHONPATH=/app
     volumes:
       - ./src/worker:/app
+      - ./src/file-processor/app:/app/app     # <- Added: shared access file-processor app
       - ./volumes/watched_files:/watched_files
     depends_on:
       - redis

src/file-processor/app/database/repositories/document_repository.py

@@ -6,9 +6,10 @@ in MongoDB with proper error handling and type safety.
 """
 
 from typing import Optional, List
+
 from bson import ObjectId
-from pymongo.errors import DuplicateKeyError, PyMongoError
 from motor.motor_asyncio import AsyncIOMotorCollection, AsyncIOMotorDatabase
+from pymongo.errors import DuplicateKeyError, PyMongoError
 
 from app.database.connection import get_extra_args
 from app.models.document import FileDocument
@@ -40,7 +41,6 @@ class FileDocumentRepository:
     """Initialize file repository with database connection."""
     self.db = database
     self.collection: AsyncIOMotorCollection = self.db.documents
-    self._ensure_indexes()
   
   async def initialize(self):
     """

src/file-processor/app/file_watcher.py

@@ -64,7 +64,7 @@ class DocumentFileEventHandler(FileSystemEventHandler):
     logger.info(f"Processing new file: {filepath}")
     
     try:
-      from tasks.document_processing import process_document
+      from tasks.main import process_document
       celery_result = process_document.delay(filepath)
       celery_task_id = celery_result.id
       logger.info(f"Dispatched Celery task with ID: {celery_task_id}")

src/file-processor/app/services/job_service.py

@@ -35,12 +35,12 @@ class JobService:
     await self.repository.initialize()
     return self
   
-  async def create_job(self, file_id: PyObjectId, task_id: Optional[str] = None) -> ProcessingJob:
+  async def create_job(self, document_id: PyObjectId, task_id: Optional[str] = None) -> ProcessingJob:
     """
     Create a new processing job.
 
     Args:
-        file_id: Reference to the file document
+        document_id: Reference to the file document
         task_id: Optional Celery task UUID
 
     Returns:
@@ -49,7 +49,7 @@ class JobService:
     Raises:
         JobRepositoryError: If database operation fails
     """
-    return await self.repository.create_job(file_id, task_id)
+    return await self.repository.create_job(document_id, task_id)
   
   async def get_job_by_id(self, job_id: PyObjectId) -> ProcessingJob:
     """

src/worker/Dockerfile

@@ -3,6 +3,12 @@ FROM python:3.12-slim
 # Set working directory
 WORKDIR /app
 
+# Install libmagic
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    libmagic1 \
+    file \
+ && rm -rf /var/lib/apt/lists/*
+
 # Copy requirements and install dependencies
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt

src/worker/requirements.txt

@@ -1,4 +1,12 @@
-
+bcrypt==4.3.0
 celery==5.5.3
-redis==6.4.0
+email-validator==2.3.0
+fastapi==0.116.1
+httptools==0.6.4
+motor==3.7.1
 pymongo==4.15.0
+pydantic==2.11.9
+redis==6.4.0
+uvicorn==0.35.0
+python-magic==0.4.27
+watchdog==6.0.0

src/worker/tasks/document_processing.py

@@ -8,81 +8,14 @@ and update processing job statuses throughout the task lifecycle.
 import logging
 from typing import Any, Dict
 
-from tasks.main import app as celery_app
+from app.config import settings
+from app.database.connection import get_database
+from app.services.document_service import DocumentService
 
 logger = logging.getLogger(__name__)
 
 
-# @celery_app.task(bind=True, autoretry_for=(Exception,), retry_kwargs={'max_retries': 3, 'countdown': 60})
+async def process_document_async(self, filepath: str) -> Dict[str, Any]:
-# def process_document(self, document_service, job_service, filepath: str) -> Dict[str, Any]:
-#   """
-#   Process a document file and extract its content.
-#
-#   This task:
-#   1. Updates the processing job status to PROCESSING
-#   2. Performs document content extraction
-#   3. Updates job status to COMPLETED or FAILED based on result
-#
-#   Args:
-#       self : Celery task instance
-#       job_service : Instance of JobService
-#       document_service : Instance of DocumentService
-#       filepath: Full path to the document file to process
-#
-#   Returns:
-#       Dictionary containing processing results
-#
-#   Raises:
-#       Exception: Any processing error (will trigger retry)
-#   """
-#   task_id = self.request.id
-#   logger.info(f"Starting document processing task {task_id} for file: {filepath}")
-#
-#   try:
-#     # Step 1: Mark job as started
-#     await job_service.mark_job_as_started(task_id=task_id)
-#     logger.info(f"Job {task_id} marked as PROCESSING")
-#
-#     # Step 2: Process the document (extract content, OCR, etc.)
-#     document = await self.document_service.create_document(filepath)
-#     logger.info(f"Created document record with ID: {document.id}")
-#
-#     result = document_service.extract_document_content(filepath)
-#     logger.info(f"Document content extracted successfully for task {task_id}")
-#
-#     # Step 3: Mark job as completed
-#     await job_service.mark_job_as_completed(task_id=task_id)
-#     logger.info(f"Job {task_id} marked as COMPLETED")
-#
-#     return {
-#         "task_id": task_id,
-#         "filepath": filepath,
-#         "status": "completed",
-#         "content_length": len(result.get("content", "")),
-#         "extraction_method": result.get("extraction_method"),
-#         "processing_time": result.get("processing_time")
-#     }
-#
-#   except Exception as e:
-#     error_message = f"Document processing failed: {str(e)}"
-#     logger.error(f"Task {task_id} failed: {error_message}")
-#
-#     try:
-#       # Mark job as failed
-#       job_service.mark_job_as_failed(task_id=task_id, error_message=error_message)
-#       logger.info(f"Job {task_id} marked as FAILED")
-#     except Exception as job_error:
-#       logger.error(f"Failed to update job status for task {task_id}: {str(job_error)}")
-#
-#     # Re-raise the exception to trigger Celery retry mechanism
-#     raise
-
-
-@celery_app.task(name="tasks.document_processing.process_document",
-                 bind=True,
-                 autoretry_for=(Exception,),
-                 retry_kwargs={'max_retries': 3, 'countdown': 60})
-def process_document(self, filepath: str) -> Dict[str, Any]:
   """
   Process a document file and extract its content.
 
@@ -93,8 +26,6 @@ def process_document(self, filepath: str) -> Dict[str, Any]:
 
   Args:
       self : Celery task instance
-      job_service : Instance of JobService
-      document_service : Instance of DocumentService
       filepath: Full path to the document file to process
 
   Returns:
@@ -106,74 +37,47 @@ def process_document(self, filepath: str) -> Dict[str, Any]:
   task_id = self.request.id
   logger.info(f"Starting document processing task {task_id} for file: {filepath}")
   
+  database = get_database()
+  document_service = DocumentService(database=database, objects_folder=settings.get_objects_folder())
+  from app.services.job_service import JobService
+  job_service = JobService(database=database)
   
-@celery_app.task(bind=True)
+  job = None
-def cleanup_old_processing_jobs(self, days_old: int = 30) -> Dict[str, Any]:
-  """
-  Clean up old processing jobs from the database.
-
-  This maintenance task removes completed and failed jobs older than
-  the specified number of days.
-
-  Args:
-      days_old: Number of days after which to clean up jobs
-
-  Returns:
-      Dictionary containing cleanup statistics
-  """
-  task_id = self.request.id
-  logger.info(f"Starting cleanup task {task_id} for jobs older than {days_old} days")
-  
-  job_service = JobService()
-  
   try:
-    # Perform cleanup
+    # Step 1: Insert the document in DB
-    cleanup_result = job_service.cleanup_old_jobs(days_old=days_old)
+    document = await document_service.create_document(filepath)
+    logger.info(f"Job {task_id} created for document {document.id} with file path: {filepath}")
     
-    logger.info(
+    # Step 2: Create a new job record for the document
-      f"Cleanup task {task_id} completed: "
+    job = await job_service.create_job(task_id=task_id, document_id=document.id)
-      f"deleted {cleanup_result['deleted_count']} jobs"
+    
-    )
+    # Step 3: Mark job as started
+    await job_service.mark_job_as_started(job_id=job.id)
+    logger.info(f"Job {task_id} marked as PROCESSING")
+    
+    # Step 4: Mark job as completed
+    await job_service.mark_job_as_completed(job_id=job.id)
+    logger.info(f"Job {task_id} marked as COMPLETED")
     
     return {
         "task_id": task_id,
+        "filepath": filepath,
         "status": "completed",
-        "deleted_count": cleanup_result["deleted_count"],
-        "days_old": days_old
     }
   
   except Exception as e:
-    error_message = f"Cleanup task failed: {str(e)}"
+    error_message = f"Document processing failed: {str(e)}"
-    logger.error(f"Cleanup task {task_id} failed: {error_message}")
+    logger.error(f"Task {task_id} failed: {error_message}")
-    raise
+    
-
+    try:
-
+      # Mark job as failed
-@celery_app.task(bind=True)
+      if job is not None:
-def get_processing_statistics(self) -> Dict[str, Any]:
+        await job_service.mark_job_as_failed(job_id=job.id, error_message=error_message)
-  """
+        logger.info(f"Job {task_id} marked as FAILED")
-  Generate processing statistics for monitoring.
+      else:
-
+        logger.error(f"Failed to process {filepath}. error = {str(e)}")
-  Returns:
+    except Exception as job_error:
-      Dictionary containing current processing statistics
+      logger.error(f"Failed to update job status for task {task_id}: {str(job_error)}")
-  """
+    
-  task_id = self.request.id
+    # Re-raise the exception to trigger Celery retry mechanism
-  logger.info(f"Generating processing statistics for task {task_id}")
-  
-  job_service = JobService()
-  
-  try:
-    stats = job_service.get_processing_statistics()
-    
-    logger.info(f"Statistics generated for task {task_id}")
-    
-    return {
-        "task_id": task_id,
-        "status": "completed",
-        "statistics": stats,
-        "timestamp": stats.get("generated_at")
-    }
-  
-  except Exception as e:
-    error_message = f"Statistics generation failed: {str(e)}"
-    logger.error(f"Statistics task {task_id} failed: {error_message}")
     raise

src/worker/tasks/main.py

@@ -3,25 +3,26 @@ Celery worker for MyDocManager document processing tasks.
 
 This module contains all Celery tasks for processing documents.
 """
-
+import asyncio
 import os
-import time
 
 from celery import Celery
 
+from tasks.document_processing import process_document_async
+
 # Environment variables
 REDIS_URL = os.getenv("REDIS_URL", "redis://localhost:6379/0")
 MONGODB_URL = os.getenv("MONGODB_URL", "mongodb://localhost:27017")
 
 # Initialize Celery app
-app = Celery(
+celery_app = Celery(
   "mydocmanager_worker",
   broker=REDIS_URL,
-  backend=REDIS_URL
+  backend=REDIS_URL,
 )
 
 # Celery configuration
-app.conf.update(
+celery_app.conf.update(
   task_serializer="json",
   accept_content=["json"],
   result_serializer="json",
@@ -33,82 +34,10 @@ app.conf.update(
 )
 
 
-@app.task(bind=True)
+@celery_app.task(bind=True, autoretry_for=(Exception,), retry_kwargs={'max_retries': 3, 'countdown': 60})
-def test_task(self, message: str):
+def process_document(self, filepath: str):
-  """
+  return asyncio.run(process_document_async(self, filepath))
-  Test task for validating worker functionality.
-
-  Args:
-      message: Test message to process
-
-  Returns:
-      dict: Task result with processing information
-  """
-  try:
-    print(f"[WORKER] Starting test task with message: {message}")
-    
-    # Simulate some work
-    for i in range(5):
-      print(f"[WORKER] Processing step {i + 1}/5...")
-      time.sleep(1)
-      
-      # Update task progress
-      self.update_state(
-        state="PROGRESS",
-        meta={
-            "current": i + 1,
-            "total": 5,
-            "message": f"Processing step {i + 1}"
-        }
-      )
-    
-    result = {
-        "status": "completed",
-        "message": f"Successfully processed: {message}",
-        "processed_at": time.time(),
-        "worker_id": self.request.id
-    }
-    
-    print(f"[WORKER] Test task completed successfully: {result}")
-    return result
-  
-  except Exception as exc:
-    print(f"[WORKER] Test task failed: {str(exc)}")
-    raise self.retry(exc=exc, countdown=60, max_retries=3)
-
-
-@app.task(bind=True)
-def process_document_task(self, file_path: str):
-  """
-  Placeholder task for document processing.
-
-  Args:
-      file_path: Path to the document to process
-
-  Returns:
-      dict: Processing result
-  """
-  try:
-    print(f"[WORKER] Starting document processing for: {file_path}")
-    
-    # Placeholder for document processing logic
-    time.sleep(2)  # Simulate processing time
-    
-    result = {
-        "status": "completed",
-        "file_path": file_path,
-        "processed_at": time.time(),
-        "content": f"Placeholder content for {file_path}",
-        "worker_id": self.request.id
-    }
-    
-    print(f"[WORKER] Document processing completed: {file_path}")
-    return result
-  
-  except Exception as exc:
-    print(f"[WORKER] Document processing failed for {file_path}: {str(exc)}")
-    raise self.retry(exc=exc, countdown=60, max_retries=3)
 
 
 if __name__ == "__main__":
-  app.start()
+  celery_app.start()